Electronic battery tester

ABSTRACT

A device for testing a battery of the type which consists of a string of individual cells includes circuitry adapted to measure a dynamic parameter of the cells or groups of cells that make up the battery. Measurements are used to construct a reference standard or to calculate a statistical parameter of a cell or group of cells that make up the battery. A output is provided which relates to the condition of the battery.

This is a Continuation-In-Part application of U.S. patent applicationSer. No. 08/943,033, filed Oct. 2, 1997 which is based on ProvisionalApplication Ser. No. 60/027,890, filed on Oct. 7, 1996.

BACKGROUND OF THE INVENTION

The present invention relates to battery testers. More specifically, thepresent invention relates to a technique for determining a parameterrelated to operation and condition of a battery.

Storage batteries, such as lead acid storage batteries of the type usedin the automotive industry, have existed for many years. However,understanding the nature of such storage batteries, how such storagebatteries operate and how to accurately test such batteries has been anongoing endeavor and has proved quite difficult. Storage batteriesconsist of a plurality of individual storage cells electricallyconnected in series. Typically each cell has a voltage potential ofabout 2.1 volts. By connecting the cells in series, the voltages of theindividual cells are added in a cumulative manner. For example, in atypical automotive storage battery, six storage cells are used toprovide a total voltage when the battery is fully charged of 12.6 volts.

There has been a long history of attempts to accurately test thecondition of storage batteries. A simple test is to measure the voltageof the battery. If the voltage is below a certain threshold, the batteryis determined to be bad. However, this test is inconvenient because itrequires the battery to be charged prior to performing the test. If thebattery is discharged, the voltage will be low and a good battery may beincorrectly tested as bad. Furthermore, such a test does not give anyindication of how much energy is stored in the battery. Anothertechnique for testing a battery is referred as a load test. In a loadtest, the battery is discharged using a known load. As the battery isdischarged, the voltage across the battery is monitored and used todetermine the condition of the battery. This technique requires that thebattery be sufficiently charged in order that it can supply current tothe load.

More recently, a technique has been pioneered by Dr. Keith S. Champlinand Midtronics, Inc. of Burr Ridge, Ill. for testing storage batteriesby measuring the conductance of the batteries. This technique isdescribed in a number of United States patents obtained by Dr. Champlin,for example, U.S. Pat. No. 3,873,911, issued Mar. 25, 1975, to Champlin,entitled ELECTRONIC BATTERY TESTING DEVICE; U.S. Pat. No. 3,909,708,issued Sep. 30, 1975, to Champlin, entitled ELECTRONIC BATTERY TESTINGDEVICE; U.S. Pat. No. 4,816,768, issued Mar. 28, 1989, to Champlin,entitled ELECTRONIC BATTERY TESTING DEVICE; U.S. Pat. No. 4,825,170,issued Apr. 25, 1989, to Champlin, entitled ELECTRONIC BATTERY TESTINGDEVICE WITH AUTOMATIC VOLTAGE SCALING; U.S. Pat. No. 4,881,038, issuedNov. 14, 1989, to Champlin, entitled ELECTRONIC BATTERY TESTING DEVICEWITH AUTOMATIC VOLTAGE SCALING TO DETERMINE DYNAMIC CONDUCTANCE; U.S.Pat. No. 4,912,416, issued Mar. 27, 1990, to Champlin, entitledELECTRONIC BATTERY TESTING DEVICE WITH STATE-OF-CHARGE COMPENSATION;U.S. Pat. No. 5,140,269, issued Aug. 18, 1992, to Champlin, entitledELECTRONIC TESTER FOR ASSESSING BATTERY/CELL CAPACITY; U.S. Pat. No.5,343,380, issued Aug. 30, 1994, entitled METHOD AND APPARATUS FORSUPPRESSING TIME VARYING SIGNALS IN BATTERIES UNDERGOING CHARGING ORDISCHARGING; U.S. Pat. No. 5,572,136, issued Nov. 5, 1996, entitledELECTRONIC BATTERY TESTER WITH AUTOMATIC COMPENSATION FOR LOWSTATE-OF-CHARGE; U.S. Pat. No. 5,574,355, issued Nov. 12, 1996, entitledMETHOD AND APPARATUS FOR DETECTION AND CONTROL OF THERMAL RUNAWAY IN ABATTERY UNDER CHARGE; U.S. Pat. No. 5,585,728, issued Dec. 17, 1996,entitled ELECTRONIC BATTERY TESTER WITH AUTOMATIC COMPENSATION FOR LOWSTATE-OF-CHARGE; U.S. Pat. No. 5,592,093, issued Jan. 7, 1997, entitledELECTRONIC BATTERY TESTING DEVICE LOOSE TERMINAL CONNECTION DETECTIONVIA A COMPARISON CIRCUIT; U.S. Pat. No. 5,598,098, issued Jan. 28, 1997,entitled ELECTRONIC BATTERY TESTER WITH VERY HIGH NOISE IMMUNITY; U.S.Pat. No. 5,757,192, issued May 26, 1998, entitled METHOD AND APPARATUSFOR DETECTING A BAD CELL IN A STORAGE BATTERY; U.S. Pat. No. 5,821,756,issued Oct. 13, 1998, entitled ELECTRONIC BATTERY TESTER WITH TAILOREDCOMPENSATION FOR LOW STATE-OF-CHARGE; and U.S. Pat. No. 5,831,435,issued Nov. 3, 1998, entitled BATTERY TESTER FOR JIS STANDARD.

Generally, in order to evaluate the condition of a battery, some type ofreference must be used with which to compare the measured parameter.Developing an accurate standard is a time-consuming process which mustbe performed on each type of battery which will be tested. Generally,the results of a battery test are only as accurate as the referencestandard being used.

SUMMARY OF THE INVENTION

A device for testing a battery of the type which consists of a string ofindividual cells includes circuitry adapted to measure a dynamicparameter of the cells or groups of cells that make up the battery.Measurements are used to construct a reference standard or to calculatea statistical parameter of a cell or group of cells that make up thebattery. A output is provided which relates to the condition of thebattery.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a table of voltage, conductance and capacity values for cellsof various strings in a battery.

FIG. 2 is a table of string parameters for various strings of a battery.

FIG. 3 is a graph of midpoint capacity difference versus midpointvoltage.

FIG. 4 is a graph of voltage versus time.

FIG. 5 is a graph of voltage versus time.

FIG. 6 is a table showing battery parameters for various strings of abattery.

FIG. 7 is a graph of capacity difference versus conductance difference.

FIG. 8 is a graph of capacity ratio versus conductance ratio.

FIG. 9 is a graph of cell capacity versus cell conductance.

FIG. 10 is a table showing accuracy of a battery test.

FIG. 11 is a graph of cell percent capacity versus cell conductance.

FIG. 12 is a graph of cell percent capacity versus cell conductance.

FIG. 13 is a simplified diagram of a device for testing a battery inaccordance with one embodiment of the present invention.

FIG. 14 is a simplified block diagram of a flow chart in accordance withone aspect of the present invention.

FIG. 15 is a simplified block diagram of a flow chart in accordance withone aspect of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention solves prior art problems associated with settingstandards, obtaining a standard and maintaining the accuracy of thestandard.

In many battery installations such as Telcos, (telephone companies), acost-effective battery system management is high priority. While aregular battery management program will ultimately reduce down time,improve customer service and system quality, programs to add capitalequipment can only be justified if a reduction in costs can be expectedthrough improved priority management or because of added valueassociated with more reliable service. There is an ongoing search formore cost effective-solutions which will help to optimize the managementof battery replacement.

Various technique have been used, including midpoint voltage monitoringtechniques and stationary monitoring systems using conductance measuringtechniques on a single cell, multicell or midpoint basis.

In order to evaluate the accuracy and utility of several monitoringtechniques, this description uses actual test data on five-48v stringsof 1000 AH VRLA AGM cells, from a telecom transmission office. The cellswere approximately 5 to 6 years old, in full float service, when tested.The data available includes individual cell float voltages, individualcell conductance measurements and complete discharge data on each of the120 cells which were discharged at the two hour rate to 1.88 volts percell. The data used for each string in the following analysis is shownin the tables of FIG. 1.

The present invention provides a new technique for establishing areference for use in a battery test. In some types of batteryinstallations, a number of battery cells are connected in a seriesstring with electrical connections on either end of the series string,as well as at least one electrical connection between the ends of thestring. The present invention recognizes that a battery can be monitoredby comparing test parameters measured between different points in thesame series of batteries. In one embodiment, the battery test isperformed between one end of the string and a midpoint, and between theother end of the string and the midpoint, and the results of the twotests are compared. Thus, instead of using an absolute standard for agiven battery, the present invention uses a relative standard andcompares one portion of the series string to another portion of theseries string.

First a midpoint voltage (MPV) technique can be evaluated for accuracy.The 24 cell string is measured in two sections, cells 1 to 12 and cells13-24. The total voltages of each half are compared and if they differby more than a previously determined amount, the MPV monitoring systemsare intended to indicate possible difficulty and/or provide an alarm. Itcan be demonstrated that in strings in which cell capacity resultsvaried from 0% to 100%, all float voltages were within themanufacturer's recommended acceptable float voltage tolerances.

For the five strings involved in this analysis, FIG. 2 shows the 12 cellfloat voltage totals for cells 1 to 12 vs. 13 to 24;the voltagedifferences, cells 13 to 24 minus cells 1 to 12; the ratios of totals,cells 13 to 24/cells 1 to 12, and similar data for the measured capacityvalues for each half string. As an additional exercise, to test thesensitivity and accuracy of the midpoint float voltage and othertechniques, the cells were rearranged in string 5, putting all the highcapacity cells in the 1 to 12 cell group and all the low capacity cellsin the 13 to 24 cell group. This resulted in an average capacity of84.3% for cells 1 to 12 vs. 48.7% for cells 13 to 24. The analysis whichfollows will include the results from this rearranged string.

Reviewing the midpoint voltage differences, it can be seen that theyrange from −0.07 volts to +0.06 volts, while capacity differences rangefrom −35.6% to +10.9% of the manufacturer's published capacity. To get abetter perspective, the capacity differences were plotted vs. themidpoint voltage differences shown in FIG. 3. A regression analysisindicates a correlation coefficient, R²=0.118, i.e., essentially nocorrelation between midpoint voltage differences and midpoint capacitydifferences. note that even in the rearranged string 5, where thecapacity difference is (48.7% minus 84.3%) equal to −35.6%, the midpointfloat voltage difference is only −0.02 volts (27.07-27.09).

Since these actual cell data does not support the effectiveness ofmidpoint voltage monitoring as a indicator of a capacity problems, itseemed worthwhile to consider some calculated scenarios in which itmight be more applicable. Information from manufacturers and nationaland international standards suggest that once stabilized and floatingproperly, VRLA cell voltages may vary by ±2.5%. For a string floating at2.25 volts per cell (VPC) average, this allows a variation of ±0.056volts. Hence, cells could float as low as 2.19 volts and as high as2.306 volts and still remain within acceptable limits. If we were totake a best (or worst) case example, putting all the low cells in 1 to12 and all the high ones in 13 to 24, would result in (12×2.306=27.672)minus (12×2.19=26.28) . The MPV is 27.672 minus 26.28 which equals a1.392 voltage difference between the two portions of the string. Sincesome users have considered a MPV differential of 1.0 volt as an alarmindicator, these results suggest that cells floating within themanufacturer's published tolerances could cause a false alarm.

It has been suggested that the MPV technique, while not useful indetecting capacity problems, could detect shorted cells. This is notnecessarily true. In most actual situations, shorted cells float atapproximately open circuit values for extended periods. For a 1.300specific gravity (SG) absorbed glass mat VRLA cell, this means 2.15volts, on float, would indicate a probable short. If one accepts the 1.0volt midpoint voltage difference as appropriate for an alarm, it is asimple calculation to determine the number of shorted cells, which mustall be in the same half of the string, to produce a one volt difference.For a strong floating at 2.25 volts per cell average, 8 shorted cells at2.15 volts, would have the remaining 16 cells at 2.30 volts. If alleight cells were in the 1 to 12 cell half, then the voltage of cells 1to 12 would be 26.4 volts vs. the voltage of cells 13 to 24 at 27.6volts, for MPV difference of 1.2 volts.

Ignoring the statistical improbability involved, note that thesensitivity of the midpoint voltage changes with the overall stringfloat voltage. For a string floating at 2.27 volts, six shorted cells,at 2.15 volts per cell would produce a midpoint voltage difference of0.96 volts. For a string floating at 2.35 volts per cell, four shortedcells would produce a voltage difference of 0.96 volts. Hence, thesensitivity to normal shorted cells of midpoint voltage is poor,requires multiple shorts in the same portion of the string and is afunction of the overall string float voltage setting.

Another possibility is a shorted cell at the unusually low float voltageof 1.95 volts. This would result in a MPV difference of only 0.32 volts,for a single shorted cell. It would require 3 cells at 1.95 volts, allin the same group to produce a MPV difference of 1.03 volts. Since a1.95 volt shorted cell is rare, three in the same group is highlyunlikely. A much less likely condition is a shorted cell at 1.0 volts,which would result in a midpoint voltage difference of 1.29 volts andcause an alarm, but again with the 1.95 volt short, a 1.0 volt short isextremely unlikely. Some experts have proposed the possibility of an“ideal” short, i.e., a cell at zero volts. Here the calculation resultsin a midpoint voltage differential of 2.34 volts, well above alarmconditions, but so unlikely as to make its detection of no practicaluse.

The result of these analyses, both on real cells with both float voltageand actual capacity values and of hypothetical values in theoreticalexercises, using difference values of voltages for shorted cells, allindicate that midpoint voltage is essentially useless as a faultdetector, except in the most unlikely circumstances.

Midpoint voltage difference monitoring during discharge has also beenproposed, with the expectation that the voltage of the lower capacityhalf, would deviate rapidly from the voltage of the stronger half. A MPValarm target of ±0.5 volts as an indicator of low capacity and plottedMPV vs. discharge time was chosen. Testing shows a significant increasein MPV as the discharge proceeded. However, careful analysis of theirdata shows that in all cases a significant percentage of overalldischarge must occur (44% to 88%) before the MPV value reached the ±0.5volts alarm point, thus causing doubt that the technique could providedefinitive results with only a brief portion of the discharge required.

The data of string #5 have been utilized to produce the graph of FIG. 4.FIG. 4 shows the battery string voltage vs. time plot and the MPVdifference vs. time. Note that the battery reached its 45.12 volt (1.88VPC) cutoff voltage in only 80 minutes, i.e., 66% of rated capacityvalue. The MPV difference did not reach the intended ±0.5 volt alarmtarget until 135 minutes, 55 minutes after the string had alreadyfailed.

In order to test the discharge MPV technique under idealized conditions,the re-configured string #5 data was then plotted, as in FIG. 5. Despitethe midpoint capacity difference of 84% vs. 48% between the two halfstrings, it still required 35 minutes of discharge time before the MPVvalue reached the ±0.5 volt MPV alarm target. This is 44% of the totaldischarge time, even under the most exaggerated capacity differencebetween the two halves of string #5. It is clear that a significantpercentage of the discharge must be performed before the MPV alarmtarget is reached. This raises serious questions as to any time or costsavings which would result from the use of this technique as a batterymonitoring device.

The present invention recognizes midpoint conductance monitoring as anaccurate and cost effective alternative. One important criteriaassociated with deploying any battery monitoring system is to identifythe demonstrated level of accuracy associated with the various testingtechniques. Included herein are several models which suggest that a usercan select from a wide variety of options available such as single ormultiple cell on-line conductance monitoring as well as single ormultiple cell on-line conductance testing using portable test equipment.The cost associated with the monitoring approach and the respectiveaccuracy of each technique will be evaluated using conductance andcapacity data for five strings shown in FIG. 1. In this assessment,individual cell conductance and capacity data are used to synthesizeequivalent conductance for 3 cell, 6 cell, and 12 cell groups. Theaverage capacity for these same equivalent cell groups are then used toassess and contrast the benefits of multiple cell monitoring.

The table of FIG. 6 lists the equivalent midpoint conductance values forcells 1 to 12 and cells 13 to 24.for the same five strings as in FIG. 1as well as for the re-configured string #5. The table also lists the 12cell conductance differences and conductance ratios. In addition, itlists the capacity differences and capacity ratios for each of the 12cell groupings in each string.

FIG. 7 shows a plot of midpoint capacity difference vs. midpointconductance difference of all of the strings, including there-configured string #5. The correlation coefficient R²=0.855 indicatesa strong correlation of midpoint capacity difference with midpointconductance difference, especially when contrasted with the R²=0.118value of the equivalent capacity/MPV regression. FIG. 8 shows a plot andregression analysis of midpoint capacity ratio vs. midpoint conductanceratio, with a correlation coefficient R²=0.834, again good correlation,far between than with MPV. Therefore, by either method chosen, midpointconductance techniques correlate far more strongly with midpointcapacity, than MPV and should therefore be far more useful as amonitoring technique. A high degree of correlation of midpointconductance with midpoint capacity once again indicates the usefulnessof midpoint conductance monitoring to predict cell state of health,without actually having to perform a discharge test. This avoidssignificant costs, scheduling difficulties and down time associated withperforming capacity discharge testing.

In order to determine the absolute accuracy of conductance monitoringtechniques, each of the five strings was analyzed on a cell by cellcapacity/conductance basis. The results were subjected to regressionanalysis, the 80% pass/fail values of conductance calculated and eachstring analyzed cell by cell to determine the accuracy of theconductance value in predicting cell pass/fail results, using the boxscore technique of previous publications.

From this data, the single cell accuracy determinations were made, i.e.:what percent of good plus bad cells were correctly identified; whatpercent of bad cells were correctly identified; what percent of badcells were missed and incorrectly called good; and what percent of goodcells were incorrectly called bad by the conductance measurements.

FIG. 9 shows an overall correlation plot of single cell percent capacityvs. single cell conductance, the R² value of 0.801 indicating goodcorrelation overall. The intersection of 80% capacity with theregression line was calculated, in order to determine the equivalentconductance value and establish the box score coordinates. For singlecells, the plot shows an overall accuracy (good called good plus badcalled bad) of 110/120=91.7%. Conductance measured two cells as goodwhich were actually at 70% and 79% capacity. It also measured eightcells as bad (9% below the 80% capacity/conductance value) which wereactually good. These values are shown in the table of FIG. 10 in theline entitled single cell.

FIG. 11 shows the overall data combined into six cell monoblocconductance and capacity values. Again, regression analysis indicatesgood correlation, R²=0.853. FIG. 11 indicates that, viewed only as sixcell monoblocs only one good monobloc (in string 4) is indicated as badby conductance, while all bad monoblocs are correctly identified byconductance. The reason for the erroneous conductance listing of string4 can easily be understood, if one returns to the single cell plot (FIG.9), where five of the cells listed as bad by conductance are from string4. The same procedures, used for the other six cell monoblocs results inthe overall data of table 3 for six cells, i.e., zero bad cells missedby conductance, 14 good cells erroneously listed as bad conductance.

A similar correlation plot is shown in FIG. 12 for the data calculatedas 12-cell monoblocs, with an R² of 0.708. FIG. 12 indicates all twelvecell monoblocs failed both conductance and capacity criteria, with noerroneous monobloc classifications. However, again using string 4 as anexample on a single cell basis, the same five cells from string 4 arelisted by conductance as bad when in fact they are good when measured assingle cells as shown in FIG. 9. Considering all ten 12-cell monoblocs atotal of 14 good cells have been listed as bad by conductance whenincluded in the overall monobloc group. These values are shown on the12-cell line of FIG. 10. The same procedures were used for each stringin blocks of 3 cells, 6 cells and 12 cells and accuracy compared to theactual single cell values. The results are shown in FIG. 10. Accuraciesof conductance in correctly detecting bad cells range from 96% to 100%from single cell through 3 and 6 cell to 12 cell blocks. Overallaccuracy of conductance correctly detecting good cells range from 93.3%for single cells to 88.3% for 12 cells blocks. Total overall accuracies,taking all erroneous values into account (good called bad, bad calledgood) indicate that conductance can accurately detect from 88.3% to91.7% of cells with both good or bad capacities. Even when used intwelve cell blocks (i.e. a 24 volt monitor), conductance showed anoverall accuracy of 88.3% or an overall inaccuracy of 11.7%. It shouldbe noted that the overall inaccuracy of 11.7% was composed entirely ofgood cells called bad. Perhaps more important is that the 12 cellgrouping showed 0% bad cells missed using the 6 to 12 cell conductancemeasurement technique in the overall 120 cell population.

As this analysis shows, the ability to monitor the conductance ofindividual cells provides the highest level of information and thereforerepresents the most informative data possible about the condition of thebattery. The individual cell resolution understandably increasesinstallation cost and design complexity and therefore the associatemonitoring system cost per string is much higher. Conversely, these datademonstrate how a much less complex and less expensive approach formonitoring 6 cell blocks or even 12 cell blocks would provide a morecost effective approach and still maintain a high level of accuracy.When a problem appears as measured by the 6 or 12 cell technique the useof individual cell conductance measurements could be used to moreaccurately identify cell conditions within the 6 to 12 cell groups.These results for 3, 6, and 12 cell monoblocs are dependent on theactual arrangement of the cells in these strings as found. Therefore theresults can not be quantitatively extrapolated to all possiblecell/monobloc or string arrangements.

In one embodiment, instead of measuring a 12-volt block of cells in aseries of battery cells and comparing the result of the measurement to astandard, the present invention compares a battery conductance ofone-half of a 48-volt battery system (i.e., 24 volts) to a second halfof the series battery system. The results of the two tests are thencompared. If the two tests differ by a predetermined percentage, analarm or other warning is provided to indicate failure of the batterystring. Further, the specific results of the test as well as therelative percentages can also be displayed, stored or otherwise actedupon.

One aspect of the invention includes the recognition that as a string ofbatteries ages, the difference in battery conductance between variousportions of the string increases. While this aspect of the inventiondoes not pinpoint the exact cell or block of cells which has caused aproblem, that information can be obtained through further batterytesting once an alarm has been provided. The invention is particularlyuseful for on-line monitoring.

The comparison between blocks of cells can be implemented as follows:

G1/G2>K  Equation 1A

or

|G1−G2|>K  Equation 1B

In this formula, G1 is the conductance of the first of one 24-volt halfof a 48-volt series string, and G2 is the conductance for the second24-volt string. Further, K is the maximum percentage ratio which ispermitted before an alarm is provided. In one embodiment, this may beten percent.

FIG. 13 is a simplified block diagram of battery test circuitry 16 inaccordance with the present invention. Apparatus 16 is shown coupled tobattery 12 which includes a positive battery terminal 22, a midpointterminal 23 and a negative battery terminal 24. Battery 12 is a storagebattery having a plurality of individual cells, for example 24, and afully charged voltage of 50.4 volts. Battery 12 is illustrated as beingformed by only two cells or groups of cells. However, any number ofcells or groups of cells can form battery 12.

Circuitry 16 operates in accordance with one embodiment of the presentinvention and determines the conductances of battery 12 betweenterminals 22,23 and between terminals 23,24. In general, the presentinvention uses measurements of dynamic parameters of the battery. Theseinclude any dynamically measured parameter, for example, conductance,resistance, admittance, reactance or impedance. Circuitry 16 includescurrent sources 50A,50B differential amplifier 52A,52B,analog-to-digital converter 54 and microprocessor 56. Amplifiers 52A,52Bare capacitively coupled to battery 12 through capacitors C₁, C₂ and C₃.Amplifiers 52A,52B have outputs connected to inputs of analog-to-digitalconverter 54. Microprocessor 56 is connected to system clock 58, memory60, and analog-to-digital converter 54. Microprocessor 56 is alsocapable of receiving an input from input device 66.

In operation, current sources 50A,50B are controlled by microprocessor56 and provide a current I in the direction shown by the arrows in FIG.12. In one embodiment, this is a square wave or a pulse. Differentialamplifiers 52A,52B are connected to terminals 22 and 23 and terminals 23and 24, respectively, of battery 12 through capacitors C₁, C₂ and C₃ andprovide outputs related to the voltage potential difference between theterminals. In a preferred embodiment, amplifiers 52A,52B have a highinput impedance.

Circuitry 16 is connected to battery 12 through a four-point connectiontechnique known as a Kelvin connection. This Kelvin connection allowscurrents I to be injected into battery 12 through a first pair ofterminals while the voltage V across the terminals is measured by asecond pair of connections. Because very little current flows throughamplifiers 52A,52B, the voltage drop across the inputs to the amplifiersis substantially identical to the voltage drop across terminals ofbattery 12. The output of the differential amplifiers 52A,52B areconverted to a digital format by A/D converter 54 and are provided tomicroprocessor 56. Microprocessor 56 operates at a frequency determinedby system clock 58 and in accordance with programming instructionsstored in memory 60.

Microprocessor 56 determines the conductance of battery 12 by applying acurrent pulse I using current source 50. The microprocessor determinesthe change in battery voltage due to the current pulse I usingamplifiers 52A, 52B and analog-to-digital converter 54. The value ofcurrent I generated by current sources 50A,50B are known and stored inmemory 60. In one embodiment, currents I are obtained by applying a loadto battery 12. Microprocessor 56 calculates the conductance of battery12 using the following equation: $\begin{matrix}{{Conductance} = {G_{BAT} = \frac{\Delta \quad I}{\Delta \quad V}}} & {{Equation}\quad 2}\end{matrix}$

where ΔI is the change in current flowing through battery 12 due tocurrent sources 50A,50B and ΔV is the change in battery voltage due toapplied current ΔI.

Microprocessor 56 operates in accordance with the present invention anddetermines two conductances: G_(BAT22,23) (the conductance betweenterminals 22 and 23) and G_(BAT23,24) (the conductance between terminals23 and 24). Microprocessor compares G_(BAT22,23) with G_(BAT23,24) inaccordance with Equation 1 and provides a warning output 62 if thedifference is more than a predetermined amount, for example, tenpercent. This can be used to signal an operator to perform additionaltesting to determine the specific cause of the fault. The warning output62 may be transmitted to a remote control station along with thespecific results or other information. Input 66 is used to inputinformation regarding battery 12, the test site, etc. and may be used toinitiate testing.

In one aspect of the invention, the measurements obtained herein arecompared against themselves over time. For example, when battery testcircuitry 16 is initially coupled to battery 12, measurements can bemade of battery 12, either the entire battery, individual cells orgroups of cells and stored in memory 60. As the battery is used, overthe course of months or years, microprocessor 56 can compare thesestored dynamic parameters against current measurements to determine ifthe overall battery is failing. In various embodiments, this is a periodof between one day and one week, one week and two weeks, two weeks andone month, one month and two moths, two months to six months, six monthsto one years, or others. With this aspect of the invention, overalldegradation of the battery can be monitored without the necessity of theinput of an external reference. The particular stored parameters can beeither the measured dynamic parameter or can be the calculatedparameters such as statistical parameters of cells or groups of cells.

The invention is also useful in detecting thermal runaway conditionswhich have been known to occur when charging a battery. A thermalrunaway condition is a feedback condition in which a battery undergoingcharge begins to heat in a manner which causes more charge to be drawn,thus causing further heating. Using the present invention, the onset ofthermal runaway may be detected when ratio between the two conductancesvaries more than a predetermined amount and halted before damaging thebattery. The invention is also advantageous because it does not requireinformation regarding an initial condition of the battery. In accordancewith the detection of thermal runaway, a current sensor 70 can beprovided to detect the flow of current I_(B) through battery 12.Differential amplifier 72 amplifies the sensed current of value which isprovided to analog to digital converter 54. Microprocessor 56 can detecta thermal runaway condition based upon a sharp increase in currentI_(B), either alone or in combination with the individual cellmeasurements, voltage across the battery or other statistics orparameters of the battery as discussed herein.

In another aspect of the present invention, microprocessor 56 constructsa reference standard based upon measurements of individual cells orgroups of cells within the string of cells which make up battery 12. Forexample, of the average of the individual conductances of the cells orgroups of cells can be obtained. If any one cell or group of cells fallsmore than a predetermined maximum amount below the average, a faultycell or group of cells is indicated. Any statistical parameter can beused and the average is simply provided as one example. Otherstatistical parameters include standard deviation, median, etc. Ingeneral, this aspect of the present invention provides a technique oftesting a battery string without requiring an external reference source.Instead, a relatively likely assumption can be made that the majority ora large portion of the individual cells in a given battery string are“good”. Based upon this assumption a number of battery cell measurementscan be used to generate the statistical parameter. The statisticalparameter is compared with individual cell measurements, either directlyor based upon a statistical parameter of the individual cellmeasurements, to determine whether a particular cell or group of cellsis “good”.

FIG. 14 is a simplified flow chart 90 of steps which are typicallyperformed by microprocessor 56 shown in FIG. 13. At block 92,microprocessor 56 obtains a first dynamic parameter of a cell or groupof cells of battery 12. A second dynamic parameter is obtained at block94 for a cell or group of cells. In accordance with the presentinvention, these groups of cells may include cells which were part ofthe measurement performed at step 92 or may be mutually exclusive. Atblock 95, microprocessor 56 computes a statistical parameter based uponthe first and second dynamic parameters. This statistical parameter iscompared to a statistical reference parameter at block 96 and at block97 the result of the comparison is output. This output may be internalto battery test circuitry 16 or may be provided visually to an operatoror as a data output from test circuitry 16.

In another aspect of the invention, a single reference is used todetermine the condition of an entire battery string. In this aspect,microprocessor 56 determines a statistical parameter of the entirestring forming battery 12 based upon individual measurements of dynamicparameters for each cell or group of cells. The statistical parametercan be any statistical parameter such as median, mean, standarddeviation, etc., in order to get a lump sum parameter related to thebattery 12. A reference standard is stored in memory 60 as appropriatefor a given statistical parameter. Any type of comparison can be usedsuch as using a window or a mathematical relationship. Microprocessor 56then is capable of determining the overall condition of battery 12 basedupon a comparison of the measured and calculated statistical parameterto the statistical reference parameter. This technique can testbatteries even in situations in which the overall battery 12 may bestill operating within an acceptable range, even though an individualcells have failed. This aspect of the invention is particularly usefulin situations where it is the overall condition of a string of batterieswhich is significant, even if individual batteries have deteriorated orfailed. Further, rather than operating on the entire string as a whole,or operating on individual battery cells or groups of cells separatelyas in the prior art, this aspect of the present invention usesindividual measurements for cells or groups of cells to compute astatistical parameter which is then compared against a referencestandard such as a reference statistical parameter.

FIG. 15 is a flow chart 100 illustrating this aspect of the presentinvention. Steps of flow chart 100 are typically implemented inmicroprocessor 56. At block 102, microprocessor 56 determines astatistical parameter for a first portion of cells in the string ofcells which make up battery 12. For example, this determination can bebased upon measurements obtained by applying a signal to battery 12 andmeasuring the resultant response signal. As described above, thisstatistical parameter can be based upon any number of dynamic parametersmeasured for different portions of the string of cells which make upbattery 12. At block 104, a first dynamic parameter is measured for acell or group of cells within the string of cells forming battery 12. Atblock 106, microprocessor compares the calculated statistical parameterto the measured first dynamic parameter and at 108 provides an outputbased upon the result of the comparison. This output can be maintainedinternally to microprocessor 56 or provided as a visual output or a dataoutput from battery test circuitry 16.

The present invention is applicable to any type of battery test.However, in one preferred embodiment, a conductance based battery testis provided. The conductance measurement may be obtained through anyappropriate technique and is not limited to the specific embodiments setforth herein. Other types of battery testing may be used including loadtesting, resistance or ohmic testing, or impedance or reactance testing.

Those skilled in the art will recognize that the invention may beimplemented in any appropriate means with additional features. Forexample, the invention may be implemented using other battery tests thanthose enumerated above. The particular comparison may also be changedand is not limited to those set forth in Equation 1. Further, theparticular string of batteries need not be divided in half to performthe test, and other permutations are within the scope of the invention.More than two strings may also be used and a more elaborate comparisontechnique implemented such as comparison against some or all of theother strings. More elaborate comparisons may be used such asstatistical and/or chronological comparisons. The testing of stringportions may also overlap such that some cells may be in more than onestring portion. The testing may be implemented using analog circuitry,software or their hybrid. As used herein, a “portion” of a string ofcells can be any subset of the string of cells, either as individualcells or as groups of cells, and need not be sequential. Dynamicparameter includes resistance, admittance, impedance, or conductance,and can be obtained by applying a signal such as a time varying signalto a cell or group of cells and measuring the response. Further, thecircuitry used to apply a signal and sense a response can be multiplexedbetween cells or groups of cells or can comprise a plurality of separatecircuits.

Although the present invention has been described with reference topreferred embodiments, workers skilled in the art will recognize thatchanges may be made in form and detail without departing from the spiritand scope of the invention.

What is claimed is:
 1. A device for testing a battery, comprising:measurement circuitry adapted to apply a signal to cells of the batteryand measure a response signal of the cells that make up the battery; anda microprocessor coupled to the measurement circuitry adapted todetermine a statistical parameter of a first portion of a string ofcells that make up the battery as a function of the response signal,measure a first dynamic parameter of a second portion of the string ofcells that make up the battery as a function of the response signal, andprovide an output based upon a comparison of the statistical parameterto the dynamic parameter.
 2. The device of claim 1 wherein thecomparison comprises a ratio of the statistical parameter to the dynamicparameter.
 3. The device of claim 1 wherein the comparison comprises asubtraction of the dynamic parameter from the statistical parameter. 4.The device of claim 1 wherein the first portion of the battery has morecells than the second portion.
 5. The device of claim 1 wherein themeasurement circuitry includes a current generator and voltagemeasurement circuitry.
 6. The device of claim 1 wherein the measurementcircuit couples to the battery through Kelvin connections.
 7. The deviceof claim 1 wherein the second portion is contained within the firstportion.
 8. The device of claim 1 wherein the second portion is notcontained within the first portion.
 9. The device of claim 1 wherein thestatistical parameter comprises average.
 10. The device of claim 1wherein the statistical parameter comprises median.
 11. The device ofclaim 1 wherein the first portion comprises a plurality of cells. 12.The device of claim 1 wherein the statistical parameter is a function ofdynamic parameters for each of the pluralities of cells.
 13. The deviceof claim 1 wherein the output is further a function of changes in thestatistical parameter over time.
 14. The device of claim 1 wherein thedynamic parameter comprises conductance.
 15. The device of claim 1wherein the dynamic parameter comprises resistance.
 16. The device ofclaim 1 wherein the dynamic parameter comprises impedance.
 17. Thedevice of claim 1 wherein the dynamic parameter comprises admittance.18. The device of claim 1 wherein the comparison is a function of astatistical parameter of dynamic parameters of the second portion.
 19. Adevice for testing a battery, comprising: measurement circuitry adaptedto apply a signal to cells of the battery and measure a response signalof the cells that make up the battery; and a microprocessor coupled tothe measurement circuitry adapted to measure a first dynamic parameterof a first portion of a string of cells that make up the battery,adapted to measure a second dynamic parameter of a second portion of thestring of cells that make up the battery, compute a statisticalparameter of the first and second dynamic parameters and provide anoutput based upon a comparison of the statistical parameter to areference.
 20. The device of claim 19 wherein the comparison comprises aratio of the statistical parameter to the reference.
 21. The device ofclaim 19 wherein the comparison comprises a subtraction of thestatistical parameter from the reference.
 22. The device of claim 19wherein the first portion of the battery has the same number of cells asthe second portion.
 23. The device of claim 19 wherein the first portionf the battery has a different number of cells than the second portion.24. The device of claim 19 wherein the measurement circuitry includes acurrent generator and voltage measurement circuitry.
 25. The device ofclaim 19 wherein the measurement circuitry couples to the batterythrough Kelvin connections.
 26. The device of claim 19 wherein thestatistical parameter comprises average.
 27. The device of claim 19wherein the statistical parameter comprises median.
 28. The device ofclaim 19 wherein the statistical parameter is a function of a dynamicparameter of a third portion of the string of cells that make up thebattery.
 29. The device of claim 19 wherein the output is further afunction of changes in the statistical parameter over time.
 30. Thedevice of claim 19 wherein the dynamic parameter comprises conductance.31. The device of claim 19 wherein the dynamic parameter comprisesresistance.
 32. The device of claim 19 wherein the dynamic parametercomprises impedance.
 33. The device of claim 19 wherein the dynamicparameter comprises admittance.
 34. A method of testing a battery withan electronic battery tester, comprising: determining a statisticalparameter for a first portion of cells in a string of cells that make upthe battery; measuring a first dynamic parameter of a second portion ofthe string of cells that make up the battery; comparing the statisticalparameter to the first dynamic parameter; and providing an output as afunction of the comparison.
 35. The method of claim 34 wherein the stepof determining a statistical parameter comprises determining dynamicparameters for a plurality of cells in the first portion.
 36. The methodof claim 34 wherein the step of determining a statistical parametercomprises determining dynamic parameters for a plurality of groups ofcells in the first portion.
 37. The method of claim 35 wherein measuringthe first dynamic parameter comprises applying a signal and measuringthe response of the battery to the signal.
 38. The method of claim 34wherein the statistical parameter comprises average.
 39. The method ofclaim 34 wherein the statistical parameter comprises median.
 40. Themethod of claim 34 wherein the dynamic parameter comprises conductance.41. A method of testing a battery with an electronic battery tester,comprising: obtaining a first dynamic parameter of a first portion of astring of cells that make up the battery; obtaining a second dynamicparameter of a second portion of the string of cells that make up thebattery; computing a statistical parameter of the first and seconddynamic parameters; comparing the statistical parameter to a reference;and providing an output as a function of the comparison.
 42. The methodof claim 41 wherein the first portion of the battery has the same numberof cells as the second portion.
 43. The method of claim 41 wherein thestatistical parameter comprises average.
 44. The method of claim 41wherein the statistical parameter comprises median.
 45. The method ofclaim 41 including obtaining a third dynamic parameter and wherein thestatistical parameter is further a function of the third dynamicparameter.
 46. The method of claim 41 wherein the dynamic parametercomprises conductance.
 47. A device for testing a battery, comprising:measurement circuitry adapted to apply a signal to cells of the batteryand measure a response signal of the cells that make up the battery; anda microprocessor coupled to the measurement circuitry adapted to measurean initial first dynamic parameter of a first portion of a string ofcells that make up the battery as a function of the response signal,store the initial dynamic parameter in memory, measure a subsequentdynamic parameter of the first portion of the string of cells that makeup the battery as a function of the response signal, and provide anoutput based upon a comparison of the initial dynamic parameter to thesubsequent dynamic parameter.